1. Satellite Remote Sensing of Tropospheric Composition
Principles, results, and challenges
Lecture at the ERCA 2012
Grenoble, February 2, 2012
Andreas Richter
Institute of Environmental Physics
University of Bremen
Bremen, Germany
( )

2. Overview What is Remote Sensing?
How can the troposphere be probed by remote sensing?
What is the sensitivity of remote sensing measurements?
A few examples for tropospheric satellite observations
What is the future of satellite remote sensing?

3. The Eye as a Remote Sensing Instrument
eye: remote sensing instrument in the visible wavelength region ( nm)
signal processing in the eye and in the brain
colour (RGB) and relative intensity are used to identify surface types
large data base and neuronal network used to derive object properties

4. The Eye as a Remote Sensing Instrument
eyes are scanning the environment with up to 60 frames per second
170° field of view, 30° focus

5. The Eye as a Remote Sensing Instrument
stereographic view, image processing, and a large data base enables detection of size, distance, and movement
!!!

6. The Eye as a Remote Sensing Instrument
the human eye is a passive remote sensing instrument, relying on (sun) light scattered from the object
no sensitivity to thermal emission of objects unlike in some other animals ?
8-14 microns image of a cat

7. The Eye as a Remote Sensing Instrument
We can also apply active remote sensing by using artificial light sources
!!!

8. Schematic of Remote Sensing Observation
Validation
Object
Changed Radiation
Radiation
Sensor
Measurement
Data Analysis
Final Result
A priori information
Forward Model

9. The Electromagnetic Spectrum
nearly all energy on Earth is supplied by the sun through radiation
wavelengths from many meters (radio waves) to nm (X-ray)
small wavelength = high energy
radiation interacts with atmosphere and surface
absorption (heating, shielding)
excitation (energy input, chemical reactions)
re-emission (energy balance)

10. Wavelength Ranges in Remote Sensing
UV: some absorptions + profile information
aerosols
vis: surface information (vegetation)
some absorptions
aerosol information
IR: temperature information
cloud information
water / ice distinction
many absorptions / emissions
+ profile information
MW: no problems with clouds
ice / water contrast
surfaces
some emissions + profile information

11. Radiative Transfer in the Atmosphere
Absorption
Scattering
Aerosol / Molecules
Emission
Scattering from a cloud
Transmission through a cloud
Scattering / reflection on a cloud
Scattering within a cloud
Cloud
Emission from a cloud
Absorption on the ground
Scattering / Reflection on the ground
Emission from the ground

12. Typical light paths: UV
Dark surface
Strong Rayleigh scattering
Most photons are scattered above absorption layer
=> Low sensitivity to BL signals!
altitude
sensitivity

13. Typical light paths: visible
Brighter surface
Significant Rayleigh Scattering
Many photons are scattered above absorption layer
=> Reduced sensitivity to BL signals!
altitude
sensitivity

14. Bright surface (snow, ice): UV and visible
Surface reflection dominates
Multiple scattering in surface layer
=> Enhanced sensitivity to BL signals!
altitude
sensitivity

15. Typical light paths: NIR
Bright surface (except for oceans)
Negligible Scattering
=> Very good sensitivity to BL signals!
altitude
sensitivity

16. Typical light paths: thermal IR
Radiation is emitted from different altitudes
Sensitivity to surface layer depends on thermal contrast
=> Usually low sensitivity to BL signals!
altitude
sensitivity

17. Thermal IR with high thermal contrast (deserts)
Radiation is emitted from different altitudes and from the surface
If surface is hotter than lower atmospheric layer, good sensitivity to BL signals!
altitude
sensitivity

18. Example: Thermal Contrast IASI
Day Night
Clerbaux, C., et al., Atmos. Chem. Phys., 9, 6041–6054, 2009
Thermal contrast (temperature difference between surface and first atmospheric layer) is highest in the morning over barren land
Vertical sensitivity varies in space and time

19. Vertical sensitivity of satellite measurements
The sensitivity of the satellite measurements depends on the altitude of the absorbing layer
This is often expressed in the form of weighting functions which give the sensitivity of the signal as function of altitude of the trace gas layer
As the vertical distribution can usually not be (completely) determined from the measurements, a priori information is needed in the retrieval
The dependence of the retrieved quantity on the real atmospheric profile depends on both, the sensitivity of the measurements and the assumptions made in the a priori
This is often expressed as averaging kernels which describe the dependence of the retrieved quantity on the amounts of trace gas in the different altitudes in the atmosphere
Comparison of satellite retrievals with other measurements are only meaningful if the averaging kernels are accounted for

20. Vertical sensitivity of satellite measurements
In the retrieval process, the vertical sensitivity is accounted for
For IR measurements, it can be well estimated from the temperature measurements
For UV/vis measurements, aerosols and surface reflectance are often a problem
Where there is no sensitivity, the a priori will be retrieved
altitude
altitude
sensitivity
concentration
Estimated sensitivity
A priori

21. Example: Averaging Kernels for CO
Depending on spectral resolution and wavelength, the number of degrees of freedom (DOFS) varies, as well as the shape of the averaging kernels
George et al., Atmos. Chem. Phys., 9, 8317–8330, 2009

22. How do we get vertical resolution in nadir IR observations?
Thermal infrared measurements have intrinsic altitude information from
Pressure broadening
Temperature dependence of line strengths
Pressure shift
The amount of vertical information depends on
Spectral resolution of the measurement
Signal to noise ratio
The molecule
Thermal contrast
Low p
High p
intensity
wavenumber

23. How do we get vertical resolution in nadir UV/vis observations?
Assimilated Stratosphere
Basic problem:
Nadir measurements contain stratospheric and tropospheric absorptions and in many cases no intrinsic vertical information

24. Clouds in UV/vis : Shielding Effect
27/04/2017
Clouds in UV/vis : Shielding Effect
50% cloud cover but only 25% surface contribution!
the part of an absorber profile situated below a cloud is basically “hidden” from view for the satellite
only through thin clouds over reflecting surfaces, sensitivity towards the lower part of the profile is still relevant
the shielding effect is larger than expected from the geometrical size of the cloud because of its brightness
Rayleigh scattering
albedo = 0.75
albedo = 0.25

25. Clouds in UV/vis : Albedo Effect
27/04/2017
Clouds in UV/vis : Albedo Effect
some photons are scattered before reaching the absorber
the part of an absorber above a cloud is better visible from space as the ratio of photons that go through it increases through the albedo effect
the lower the cloud, the larger the effect
in the UV this is more important than in the visible as Rayleigh scattering is proportional to -4
Rayleigh scattering
most photons are absorbed on the ground
albedo = 0.25

26. Clouds in UV/vis : Albedo Effect
27/04/2017
Clouds in UV/vis : Albedo Effect
many photons are scattered below the absorber
the part of an absorber above a cloud is better visible from space as the ratio of photons that go though it increases through the albedo effect
the lower the cloud, the larger the effect
in the UV this is more important than in the visible as Rayleigh scattering is proportional to -4
Rayleigh scattering
albedo = 0.75
albedo = 0.25

27. Effect of Spatial Resolution: Example NO2
OMI: 13:30 LT
For species with short atmospheric life time, horizontal variability is large
Spatial resolution of sensor is relevant for interpretation
Spatial resolution also influences cloud fraction
Time of overpass may also play a role!

28. Satellite Orbits (Near) Polar Orbit: orbits cross close to the pole
global measurements are possible
low earth orbit LEO (several 100 km)
ascending and descending branch
special case: sun-synchronous orbit:
overpass over given latitude always at the same local time, providing similar illumination
for sun-synchronous orbits: day and night branches
Geostationary Orbit:
satellite has fixed position relative to the Earth
parallel measurements in a limited area from low to middle latitudes
km flight altitude, equatorial orbit

29. Why do we need satellite measurements?
not all measurement locations are accessible (atmosphere, ice, ocean)
remote sensing facilitates analysis of long time series and extended measurement areas
for many phenomena, global measurements are needed
remote sensing measurements usually can be automated
often, several parameters can be measured at the same time
on a per measurement basis, remote sensing measurements usually are less expensive than in-situ measurements

30. What is problematic about satellite measurements?
remote sensing measurements are always indirect measurements
the electromagnetic signal is often affected by more things than just the quantity to be measured
usually, additional assumptions and models are needed for the interpretation of the measurements
usually, the measurement area / volume is relatively large
validation of remote sensing measurements is a major task and often not possible in a strict sense
estimation of the errors of a remote sensing measurement often is difficult

31. Comparison of different observation options
Nadir:
view to the surface
good spatial resolution
little vertical resolution
Limb:
good vertical resolution,
but only in the UT/LS region
large cloud probability
UV/vis/NIR:
sensitivity down to surface
relevant species observable
limited number of species
daytime only
no intrinsic vertical resolution in nadir
aerosols introduce uncertainties in light path
IR:
large number of potential species
day and night measurements
some vertical resolution in nadir
weighted towards middle troposphere
problems with strong absorbers
problems with dark (solar IR) or cold (thermal IR) surfaces

32. MOPITT
Instrument: IR gas correlation spectrometer with pressure modulation
Operational since March 2000
Spatial resolution: 22 x 22 km2
Day + night measurements
Global coverage: 3.5 days
Species: CO (1 – 2 DOFS)

33. MOPITT CO column January 2009
CO total column [1018 moelc cm-2]
Hemispheric gradient
Topography
Pollution in Asia
Biomass burning in Africa

34. TOMS Instrument: UV discrete (6) wavelengths grating spectrometer
Operational: October
Spatial resolution: 50 x 50 km2
Global coverage: 1.5 days
Species: O3, SO2

35. TOMS: Ozone columns
Large scale tropospheric ozone patterns retrieved using the cloud slicing method
During El Nino year, clear ozone maximum over Indonesia
Origins: photochemical smog from biomass burning and change in circulation pattern
Ziemke, J. R et al., (2001), “Cloud slicing”: A new technique to derive upper tropospheric ozone from satellite measurements, J. Geophys. Res., 106(D9), 9853–9867

36. GOME / GOME-2 Instrument: 4 channelUV/vis grating spectrometer GOME-2
Operational on ERS –
Spatial resolution 320 x 40 km2
Global coverage: 3 days
Species: O3, NO2, HCHO, CHOCHO, BrO, IO, SO2, H2O
GOME-2
on MetOp since
80 x 40 km2
1.5 days

37. GOME: Polar springtime BrO
Richter, A. et al., GOME observations of tropospheric BrO in Northern Hemispheric spring and summer 1997, Geophys. Res. Lett., No. 25, pp , 1998.
Large regions of enhanced boundary layer BrO in polar spring
Autocatalytic release of Br from sea salt from aerosols / frost flowers / ice surfaces
Rapid ozone destruction and link to Hg chemistry

38. SCIAMACHY
scanner modules
telescope
pre-disperser
UV channels 1-2
Vis channels 3-4
NIR channels 5-6
SWIR channels 7-8
Instrument: 8 channel UV/vis/NIR grating spectrometer nadir, limb + occultation measurements
Operational on ENVISAT since
Spatial resolution (30) 60 x 30 km2
Global coverage: 6 days
Species: O3, NO2, HCHO, CHOCHO, BrO, IO, SO2, H2O, CH4, CO2, CO

39. SCIAMACHY: Methane: The missing tropical source
SCIAMACHY measurements and atmospheric models agree well over most of the globe
In the tropics, the model underestimates SCIAMACHY measurements
This indicates a tropical CH4 source missing in current models
Important to assess impact of anthropogenic activities
Effect is smaller using current satellite data version but still there
SCIAMACHY – TM3
TM3 (model)
Frankenberg et al., science, 308. no. 5724, pp DOI: /science , 2005

40. SCIAMACHY: CO2 in the Northern Hemisphere
Buchwitz et al., ACP, 2007;
Schneising et al., ACP, 2008
Detection of annual cycle
Detection of year-to-year increase
Detection of spatial variability
Not yet accurate enough for Kyoto monitoring on country level

41. OMI Instrument: UV/vis imaging grating spectrometer (push-broom)
Operational on Aura since October 2004
Spatial resolution: up to 13 x 24 km2
Global coverage: 1 day
Species: O3, NO2, HCHO, CHOCHO, BrO, SO2

42. OMI: SO2 columns SO2 signals from volcanoes in Ecuador and Columbia–
SO2 signals from volcanoes in Ecuador and Columbia
Clear signature of Peruvian copper smelters
Very large sources of local pollution
Effect of (temporary) shut down and (permanent) implementation of emission reductions (H2SO4 production) can be monitored
Carn, S. A., et al., t (2007), Sulfur dioxide emissions from Peruvian copper smelters detected by the Ozone Monitoring Instrument, Geophys. Res. Lett., 34, L09801, doi: /2006GL

43. IASI Instrument: IR Fourier Transform Spectrometer, 0.5 cm-1
Clerbaux, C., et al., Atmos. Chem. Phys., 9, 6041–6054, 2009
Instrument: IR Fourier Transform Spectrometer, 0.5 cm-1
Operational on MetOp since January 2007
Spatial resolution: circular, 12 km diameter
Global coverage 2x per day (day and night)
Species: H2O, HDO, CH4, O3, CO, HNO3, NH3, CH3OH, HCOOH, C2H4, SO2, CO2, N2O, CFC-11, CFC-12, HCF-22, OCS, ...

44. Clarisse et al., nature geoscience, doi:10.1038/ngeo551, 2009
IASI: NH3
Clarisse et al., nature geoscience, doi: /ngeo551, 2009
First global measurement of Ammonia
Ammonia hot-spots where intense agriculture / livestock leads to high emissions
Relevant for particulate formation and acidification / eutrophication

45. Summary and Conclusions
Satellite observations of tropospheric composition in the UV/vis, NIR and thermal IR provide consistent global datasets for many species including major air pollutants such as O3, CO, NO2, and HCHO
The measurements are averaged horizontally and vertically which makes them difficult to compare to point measurements
Remote sensing in an indirect method that necessitates use of a priori information in the data retrieval which has an impact on the results
Visible and NIR measurements provide good sensitivity to the boundary layer, the thermal IR has intrinsic vertical information
In spite of the relative large uncertainties involved in satellite remote sensing , they provide a unique source of information on the composition of the troposphere

46. What is the future of satellite measurements of tropospheric trace gases?
Satellite measurements will be improved by
Better spatial resolution
Better temporal resolution (geostationary observations)
Better coverage of species and vertical resolution (extension of the wavelengths covered (from UV to IR)
Better precision (higher spectral resolution in the IR)
High vertical resolution (active systems)
The usefulness of satellite data will be improved by better integration with other measurements
Satellite data will be strongly integrated in atmospheric models

47. Active measurements: CALIOP aerosol

48. Thank you for your attention
and
questions please!